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Modeling contribution to risk assessment of thermal production power for geothermal reservoirs
(2013)
We present an effective finite difference formulation for implementing and modeling multiple borehole heat exchangers (BHE) in the general 3-D coupled heat and flow transport code SHEMAT. The BHE with arbitrary length can be either coaxial or double U-shaped. It is particularly suitable for modeling deep BHEs which contain varying pipe diameters and materials.
Usually, in numerical simulations, a fine discretization of the BHE assemblage is required, due to the large geometric aspect ratios involved. This yields large models and long simulation times. The approach avoids this problem by considering heat transport between fluid and the soil through pipes and grout via thermal resistances. Therefore, the simulation time can be significantly reduced.
The coupling with SHEMAT is realized by introducing an effective heat generation. Due to this connection, it is possible to consider heterogeneous geological models, as well as the influence of groundwater flow. This is particularly interesting when studying the long term behavior of a single BHE or a BHE field. Heating and cooling loads can enter the model with an arbitrary interval, e.g. from hourly to monthly values. When dealing with large BHE fields, computing times can be further significantly reduced by focusing on the temperature field around the BHEs, without explicitly modeling inlet and outlet temperatures. This allows to determine the possible migration of cold and warm plumes due to groundwater flow, which is of particular importance in urban areas with a high BHE installation density.
The model is validated against the existing BHE modeling codes EWS and EED. A comparison with monitoring data from a deep BHE in Switzerland shows a good agreement. Synthetic examples demonstrate the field of application of this model.
The proposed Den Haag Zuidwest district heating system of the city of The Hague consists of a deep doublet in a Jurassic sandstone layer that is designed for a production temperature of 75 °C and a reinjection temperature of 40 °C at a flow rate of 150 m3 h−1. The prediction of reservoir temperature and production behavior is crucial for success of the proposed geothermal doublet. This work presents the results of a study of the important geothermal and geohydrological issues for the doublet design. In the first phase of the study, the influences of the three-dimensional (3D) structures of anticlines and synclines on the temperature field were examined. A comprehensive petrophysical investigation was performed to build a large scale 3D-model of the reservoir. Several bottomhole temperatures (BHTs), as well as petrophysical logs were used to calibrate the model using thermal conductivity measurements on 50 samples from boreholes in different lithological units in the study area. Profiles and cross sections extracted from the calculated temperature field were used to study the temperature in the surrounding areas of the planned doublet. In the second phase of the project, a detailed 3D numerical reservoir model was set up, with the aim of predicting the evolution of the producer and injector temperatures, and the extent of the cooled area around the injector. The temperature model from the first phase provided the boundary conditions for the reservoir model. Hydraulic parameters for the target horizons, such as porosity and permeability, were taken from data available from the nearby exploration wells. The simulation results are encouraging as no significant thermal breakthrough is predicted. For the originally planned location of the producer, the extracted water temperature is predicted to be around 79 °C, with an almost negligible cooling in the first 50 years of production. When the producer is located shallower parts of the reservoir, the yield water temperatures is lower, starting at ≈76 °C and decreasing to ≈74 °C after 50 years of operation. This comparatively larger decrease in temperature with time is caused by the structural feature of the reservoir, namely a higher dip causes the cooler water to easily move downward. In view of the poor reservoir data, the reservoir simulation model is constructed to allow iterative updates using data assimilation during planned drilling, testing, and production phases. Measurements during an 8 h pumping test carried out in late 2010 suggest that a flow rate of 150 m3 h−1 is achievable. Fluid temperatures of 76.5 °C were measured, which is very close to the predicted value.
Numerische Simulation des Gefrierprozesses bei der Baugrundvereisung im durchströmten Untergrund
(2008)
Quantifying and minimizing uncertainty is vital for simulating technically and economically successful geothermal reservoirs. To this end, we apply a stochastic modelling sequence, a Monte Carlo study, based on (i) creating an ensemble of possible realizations of a reservoir model, (ii) forward simulation of fluid flow and heat transport, and (iii) constraining post-processing using observed state variables. To generate the ensemble, we use the stochastic algorithm of Sequential Gaussian Simulation and test its potential fitting rock properties, such as thermal conductivity and permeability, of a synthetic reference model and—performing a corresponding forward simulation—state variables such as temperature. The ensemble yields probability distributions of rock properties and state variables at any location inside the reservoir. In addition, we perform a constraining post-processing in order to minimize the uncertainty of the obtained distributions by conditioning the ensemble to observed state variables, in this case temperature. This constraining post-processing works particularly well on systems dominated by fluid flow. The stochastic modelling sequence is applied to a large, steady-state 3-D heat flow model of a reservoir in The Hague, Netherlands. The spatial thermal conductivity distribution is simulated stochastically based on available logging data. Errors of bottom-hole temperatures provide thresholds for the constraining technique performed afterwards. This reduce the temperature uncertainty for the proposed target location significantly from 25 to 12 K (full distribution width) in a depth of 2300 m. Assuming a Gaussian shape of the temperature distribution, the standard deviation is 1.8 K. To allow a more comprehensive approach to quantify uncertainty, we also implement the stochastic simulation of boundary conditions and demonstrate this for the basal specific heat flow in the reservoir of The Hague. As expected, this results in a larger distribution width and hence, a larger, but more realistic uncertainty estimate. However, applying the constraining post-processing the uncertainty is again reduced to the level of the post-processing without stochastic boundary simulation. Thus, constraining post-processing is a suitable tool for reducing uncertainty estimates by observed state variables.
Capacitive field-effect electrolyte-insulator-semiconductor sensors consisting of an Al-p-Si-SiO2 structure have been used for the electrical detection of unlabelled single- and double-stranded DNA (dsDNA) molecules by their intrinsic charge. A simple functionalization protocol based on the layer-by-layer (LbL) technique was used to prepare a weak polyelectrolyte/probe-DNA bilayer, followed by the hybridization with complementary target DNA molecules. Due to the flat orientation of the LbL-adsorbed DNA molecules, a high sensor signal has been achieved. In addition, direct label-free detection of in-solution hybridized dsDNA molecules has been studied.
The chemical imaging sensor is a field-effect sensor which is able to visualize both the distribution of ions (in LAPS mode) and the distribution of impedance (in SPIM mode) inthe sample. In this study, a novel wound-healing assay is proposed, in which the chemical imaging sensor operated in SPIM mode is applied to monitor the defect of a cell layer brought into proximity of the sensing surface.A reduced impedance inside the defect, which was artificially formed ina cell layer, was successfully visualized in a photocurrent image.
A sensor system for investigating (bio)degradationprocesses of polymers is presented. The system utilizes semiconductor field-effect sensors and is capable of monitoring the degradation process in-situ and in real-time. The degradation of the polymer poly(d,l-lactic acid) is exemplarily monitored in solutions with different pH value, pH-buffer solution containing the model enzyme lipase from Rhizomucormiehei and cell-culture medium containing supernatants from stimulated and non-stimulated THP-1-derived macrophages mimicking activation of the immune system.
An amperometric enzyme biosensor has been applied for the detection of adrenaline. The adrenaline biosensor has been prepared by modification of an oxygen electrode with the enzyme laccase that operates at a broad pH range between pH 3.5 to pH 8. The enzyme molecules were immobilized via cross-linking with glutaraldehyde. The sensitivity of the developed adrenaline biosensor in different pH buffer solutions has been studied.
LAPS are field-effect-based potentiometric sensors which are able to monitor analyte concentrations in a spatially resolved manner. Hence, a LAPS sensor system is a powerful device to record chemical imaging of the concentration of chemical species in an aqueous solution, chemical reactions, or the growth of cell colonies on the sensor surface, to record chemical images. In this work, multi-chamber 3D-printed structures made out of polymer (PP-ABS) were combined with LAPS chips to analyse differentially and simultaneously the metabolic activity of Escherichia coli K12 and Chinese hamster ovary (CHO) cells, and the responds of those cells to the addition of glucose solution.
Allgemeines Steuerrecht
(2015)
Various models have been proposed for the prediction of the necessary support pressure at the face of a shallow tunnel. To assess their quality, the collapse of a tunnel face was modelled with small-scale model tests at single gravity. The development of the failure mechanism and the support force at the face in dry sand were investigated. The observed displacement patterns show a negligible influence of overburden on the extent and evolution of the failure zone. The latter is significantly influenced, though, by the initial density of the sand: in dense sand a chimney-wedge-type collapse mechanism developed, which propagated towards the soil surface. Initially, loose sand did not show any discrete collapse mechanism. The necessary support force was neither influenced by the overburden nor the initial density. A comparison with quantitative predictions by several theoretical models showed that the measured necessary support pressure is overestimated by most of the models. Those by Vermeer/Ruse and Léca/Dormieux showed the best agreement to the measurements.
This paper proposes an approach to the choice and evaluation of engineering models with the aid of a typical application in geotechnics. An important issue in the construction of shallow tunnels, especially in weak ground conditions, is the tunnel face stability. Various theoretical and numerical models for predicting the necessary support pressure have been put forth in the literature. In this paper, we combine laboratory experiments performed at the University of Innsbruck with current methods of uncertainty and sensitivity analysis for assessing adequacy, predictive power and robustness of the models. The major issues are the handling of the twofold uncertainty of test results and of model predictions as well as the decision about what are the influential input parameters.
Influence of refrigerated storage on tensile mechanical properties of porcine liver and spleen
(2015)
Detection of triacetone triperoxide using temperature cycled metal-oxide semiconductor gas sensors
(2015)
A concept for a new generation of an integrated multi-functional biosensor/actuator system is developed, which is based on biomolecular logic principles. Such a system is expected to be able to detect multiple biochemical input signals simultaneously and in real-time and convert them into electrical output signals with logical operations such as OR, AND, etc. The system can be designed as a closed-loop drug release device triggered by an enzyme logic gate, while the release of the drug induced by the actuator at the required dosage and timing will be controlled by an additional drug sensor. Thus, the system could help to make an accurate and specific diagnosis. The presented concept is exemplarily demonstrated by using an enzyme logic gate based on a glucose/glucose oxidase system, a temperature-responsive hydrogel mimicking the actuator function and an insulin (drug) sensor. In this work, the results of functional testing of individual amperometric glucose and insulin sensors as well as an impedimetric sensor for the detection of the hydrogel swelling/shrinking are presented.
A new microfluidic assembly method for semiconductor-based biosensors using 3D-printing technologies was proposed for a rapid and cost-efficient design of new sensor systems. The microfluidic unit is designed and printed by a 3D-printer in just a few hours and assembled on a light-addressable potentiometric sensor (LAPS) chip using a photo resin. The cell growth curves obtained from culturing cells within microfluidics-based LAPS systems were compared with cell growth curves in cell culture flasks to examine biocompatibility of the 3D-printed chips. Furthermore, an optimal cell culturing within microfluidics-based LAPS chips was achieved by adjusting the fetal calf serum concentrations of the cell culture medium, an important factor for the cell proliferation.
Chelate stabilization of a titanium(IV)–salan alkoxide by ligand exchange with 2,6-pyridinedicarboxylic acid (dipic) resulted in heptacoordinate complex 3 which is not redox-active, stable on silica gel and has increased aqueous stability. 3 is highly toxic in HeLa S3 and Hep G2 and has enhanced antitumor efficacy in a mouse cervical-cancer model.
Persistent infection with high-risk human papillomaviruses (hrHPV) can result in the formation of anogenital cancers. As hrHPV proteins E6 and E7 are required for cancer initiation and maintenance, they are ideal targets for immunotherapeutic interventions. Previously, we have described the development of DNA vaccines for the induction of HPV16 E6 and E7 specific T cell immunity. These vaccines consist of ‘gene-shuffled’ (SH) versions of HPV16 E6 and E7 that were fused to Tetanus Toxin Fragment C domain 1 (TTFC) and were named TTFC-E6SH and TTFC-E7SH. Gene-shuffling was performed to avoid the risk of inducing malignant transformation at the vaccination site. Here, we describe the preclinical safety evaluation of these candidate vaccines by analysis of their transforming capacity in vitro using established murine fibroblasts (NIH 3T3 cells) and primary human foreskin keratinocytes (HFKs). We demonstrate that neither ectopic expression of TTFC-E6SH and TTFC-E7SH alone or in combination enabled NIH 3T3 cells to form colonies in soft agar. In contrast, expression of HPV16 E6WT and E7WT alone or in combination resulted in effective transformation. Similarly, retroviral transduction of HFKs from three independent donors with both TTFC-E6SH and TTFC-E7SH alone or in combination did not show any signs of immortalization. In contrast, the combined expression of E6WT and E7WT induced immortalization in HFKs from all donors. Based on these results we consider it justified to proceed to clinical evaluation of DNA vaccines encoding TTFC-E6SH and TTFC-E7SH in patients with HPV16 associated (pre)malignancies.
Efficient FACS selection procedure for cells undergoing Flp-mediated site-specific conversions
(1998)
Transcription-promoting genomic sites in mammalia: their elucidation and architectural principles
(1998)